You're reading from Engineering Data Mesh in Azure Cloud

Product typeBook

Published inMar 2024

PublisherPackt

ISBN-139781805120780

Edition1st Edition

Concepts

Data Science

Author (1)

Aniruddha Deswandikar

Summary

In this chapter, we looked at what master data is and the importance of clean master data for generating accurate analytics. We looked at some of the main reasons why master data drifts from its original and correct values. We then looked at various patterns for maintaining master data and how master data can be accessed in a data mesh scenario with distributed analytics. MDM systems can be complex to build and maintain. We saw the pros and cons of building versus buying an MDM system.

In the next chapter, we will understand monitoring and data observability.

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Engineering Data Mesh in Azure Cloud

Published in: Mar 2024Publisher: PacktISBN-13: 9781805120780

Author (1)

Aniruddha Deswandikar

Aniruddha Deswandikar holds a Bachelor's degree in Computer Engineering and is a seasoned Solutions Architect with over 30 years of industry experience as a developer, architect and technology strategist. His experience spans from start-ups to dotcoms to large enterprises. He has spent 18 years at Microsoft helping Microsoft customers build their next generation Applications and Data Analytics platforms. His experience across Application, Data and AI has helped him provide holistic guidance to companies large and small. Currently he is helping global enterprises set up their Enterprise-scale Analytical system using the Data Mesh Architecture. He is a Subject Matter Expert on Data Mesh in Microsoft and is currently helping multiple Microsoft Global Customers implement the Data Mesh architecture.
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